Our fast-growing team is seeking a Data Engineer to support our teams by ensuring high quality of the data used for the machine learning training and evaluation tasks. Your responsibilities will include the following:
- Automation and scaling of everyday data processing tasks: acquisition, storage, preparation for machine learning and evaluation, data preparation for other use cases.
- Acquisition and storage: ensure data is accessible to users in desired formats; keep track of what data we have and relevant metadata (such as recording parameters, weather conditions etc).
- Preparation for machine learning: automate data selection, evaluation of annotated data; convert annotated data to ML-ready datasets.
- Ensuring data quality and quality of the training: implement relevant data quality metrics; automate data comparison .
Preferred Qualifications and Experience:
- Computer science, mathematics, or other relevant engineering/science background.
- Excellent knowledge of at least one scripting programming language; ability to quickly write efficient shell scripts for everyday data-related tasks.
- Experience developing large-scale data processing pipelines that multiple teams/products depend on.
- Ability to reason about data in quantitative terms.
Experience in aerospace engineering or avionics is not required; we will teach you everything you need to know about the constraints of safety critical systems in airworthy applications.
- Combine the best of both worlds: a) work in fast-growing startup and b) collaborate with and learn from very experienced engineers and scientists that have previously worked at Google, SpaceX, CERN, Imperial College, and ETH Zürich.
- Build cutting-edge technology that will shape our future.
- Join our pilots to test your ideas in the air during test flights in the Swiss Alps.
- Develop scarce and marketable skills in machine learning, computer vision and robotics that are relevant beyond aviation (e.g., autonomous driving, medical applications, pharmaceuticals)
How to Apply:
Send your Resume/CV, including your portfolio of projects to email@example.com
. Tell us a bit about yourself, why you think you are a good fit for us and why we are a good fit for you.